By: Emily Durning
Through my involvement with Responsible Data Science @ Pitt [now the hub for AI and Data Science Leadership, HAIL], I was able to attend the makerspace sessions of the Equity and Access in Algorithms, Mechanics, and Optimization (EAAMO) conference this past semester. While my knowledge of the conference was limited going into the Synthesis Session at the end of the second day, I had a great time immersing myself in the conversations around measuring different interpretations of “progress” with the “Social Indicators” breakout group. The goal of this session was to review notes from a breakout session earlier in the day, pick out the main themes and ideas identified, and pose new questions to further the discussion the following day.
As I had not been present for the initial discussion, I took a backseat during the beginning of the synthesis session. It was clear that everyone involved was excited and energized by the conversations they had been a part of throughout the day. I felt lucky to be able to enter the conference at the end of the day, with a fraction of the attendees present, and see the behind the scenes. Very quickly, the theme of small wins was identified. For those close to a project or doing the hands on work, small wins are motivators, and indicators of success. For those funding a project or further removed from the day to day work, these small wins do not have the monetary value they want to see. We left that night with discussion questions prepared for the next day, all with the goal of learning what are considered small wins in different fields, and how can stakeholders be encouraged to appreciate these small wins more?
On the last day of the conference, I attended the final MakerSpace session. I was finally able to put faces to those whose thoughts I had analyzed the night before, and with a stronger handle on the content and goal of this session, was able to participate more. As it often is with these sorts of discussions, time passed too quickly, and before we knew it, we were asked to present our final thoughts. After hearing from the table about the small wins they see in their field, we moved to how to translate these small wins. Our ending notes presented to the conference recapped this discussion, while pointing future discussions towards the idea of “decoding” what impact unexpected small wins will have on a larger success, and how the value in these wins can be communicated.
Thank you to Emily Durning for sharing her reflections on the EAAMO conference and the Social Indicators makerspace sessions. We're grateful for her curiosity and thoughtful engagement, and for representing HAIL (formerly Responsible Data Science @ Pitt) at this event.